Patient data mining for clinical trials

ABSTRACT

The present invention provides a system and method for selecting prospective patients for a clinical trial. In various embodiments, a clinical trials brokerage is configured to receive requests from drug companies for lists of persons meeting specified criteria for clinical trials. Patient records are retrieved from a structured computerized patient record (CPR) data warehouse populated with comprehensive patient information mined from unstructured hospital records. A list of persons for whom consent was obtained can be outputted and forwarded to the entity interested in performing the clinical trial and which requested the list. Anonymity of a patient can be maintained until the patient provides consent to participate in the clinical trial.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser.No. 60/335,542, filed on Nov. 2, 2001, which is incorporated byreference herein in its entirety.

FIELD OF THE INVENTION

The present invention relates to medical information processing systems,and, more particularly to a computerized system and method for selectingpersons for clinical trials.

BACKGROUND OF THE INVENTION

Selection of persons for clinical trials is an expensive process. It isestimated that it costs drug companies several thousand dollars for eachparticipant selected. Furthermore, sometimes even after being selected,persons must be dropped from a trial because of inaccurate or incorrectinformation. This may delay the trial, causing an even greater expense.

Although drug companies try to get the word out by placingadvertisements or through direct contact with physicians, the selectionprocess is generally quite inefficient. Physicians tend to be busy anddo not always have time to respond to requests for patients, andpatients may not see the advertisements for clinical trials or subscribeto the periodicals where they are placed.

Moreover, physicians at a specialized medical center tend to referpatients to trials sponsored at that center. Many physicians are unawareof all the available clinical trials because of the time it takes tokeep current on all available trials for every patient that thephysician sees.

In addition, clinical trials often call for very specific selectioncriteria and it may be difficult to ascertain if a particular personqualifies for a trial. Furthermore, because hospitals typically storeinformation in an unstructured manner, it may be impossible usinghospital records to select patients qualifying for particular clinicaltrials.

An equally important problem is that of matching clinical trials tospecific patients. For example, for cancer alone, at any point in timethere are over 600 trials in progress. Statistics show that clinicaltrial web sites total 75,000 hits every week, mostly from patientsseeking information about trials, who are trying to fet added to atrial. Estimates from National Cancer Institute indicate that only twopercent of those patients eligible for a trial are in a trial. Thus, itis critically important for an individual to know if he or she may beeligible for a trial.

Given the importance and expense of selecting qualified persons forclinical trials, it would be desirable and highly advantageous toprovide improved techniques for automatically selecting prospectiveparticipants for clinical trials.

SUMMARY OF THE INVENTION

The present invention provides a technique for selecting prospectiveparticipants in a clinical trial.

In various embodiments of the present invention, a method is providedthat includes receiving a request for a list of prospective participantsmeeting specified criteria for a clinical trial. A set of patientrecords is then retrieved to determine persons meeting the specifiedcriteria.

The specified criteria may include probability information, thusallowing the selection of patients likely to meet the specified criteriafor the clinical study (e.g., 90% likelihood of diabetes, 70% likelihoodof hypertension). In this case, the relevant patient records wouldinclude probabilistic information to allow for such selection.Additional information for each prospective participant may also beretrieved. This additional information may include information aboutother clinical trials that the person participated in, including whethera placebo was administered.

Furthermore, persons may still be selected even though not allinformation needed to determine whether a person qualifies in allrespects for a clinical trial is present.

Consent to participate in a clinical trial should be obtained. A list ofpersons for whom consent was obtained can be outputted and forwarded toan entity interested in performing the clinical trial. Typically, thisis a drug company. Physicians may be notified of their InstitutionalReview Board (IRB) statuses (e.g., ‘approved’, ‘pending’, or ‘notapproved’. Expiration dates of their status may be forwarded to approvedphysicians.

Because patient confidentiality is important, the anonymity of a personmeeting the specified criteria must be preserved. The process ofobtaining consent may include selecting physicians associated with thepersons meeting the specified criteria, requesting approval toparticipate from each of the selected physicians, and providing consentinformation to persons meeting the specified criteria whose physicianprovided approval to participate in the clinical trial.

To further facilitate the process, questionnaires may be provided. Thesequestionnaires may be used to ascertain qualifications for the clinicaltrial.

Additionally, compensation and fees can be determined for the partiesinvolved. For example, participating physicians may be compensated. Theentity requesting the list may be charged a fee. The patientsparticipating in the clinical trial may also be compensated.

The data source used to determine the persons eligible for the clinicaltrial may include a data warehouse. Further, it may be populated withstructured information obtained from mining unstructured patientrecords. The patient records may include patient information obtainedfrom a plurality of participating health care providers, such ashospitals.

In various alternative embodiments of the present invention, a systemfor selecting prospective clinical trials for an individual patient isprovided. The system includes a clinical trials database, a data sourcecontaining patient information, and a clinical trials brokerage forgenerating a list of clinical trials for patients meeting specifiedcriteria associated with the clinical trials. At least some of theinformation in the data source containing patient information may beobtained from mining unstructured patient records.

These and other aspects, features and advantages of the presentinvention will become apparent from the following detailed descriptionof preferred embodiments, which is to be read in connection with theaccompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a computer processing system to which thepresent invention may be applied according to an embodiment of thepresent invention;

FIG. 2 shows an exemplary clinical trials brokerage system according toan embodiment of the present invention;

FIG. 3 shows an exemplary clinical trials brokerage system according toanother embodiment of the present invention; and

FIG. 4 shows a flow diagram outlining an exemplary technique forselecting a person for a clinical trial according to an embodiment ofthe present invention.

DESCRIPTION OF PREFERRED EMBODIMENTS

To facilitate a clear understanding of the present invention,illustrative examples are provided herein which describe certain aspectsof the invention. However, it is to be appreciated that theseillustrations are not meant to limit the scope of the invention, and areprovided herein to illustrate certain concepts associated with theinvention.

It is also to be understood that the present invention may beimplemented in various forms of hardware, software, firmware, specialpurpose processors, or a combination thereof. Preferably, the presentinvention is implemented in software as a program tangibly embodied on aprogram storage device. The program may be uploaded to, and executed by,a machine comprising any suitable architecture. Preferably, the machineis implemented on a computer platform having hardware such as one ormore central processing units (CPU), a random access memory (RAM), andinput/output (I/O) interface(s). The computer platform also includes anoperating system and microinstruction code. The various processes andfunctions described herein may either be part of the microinstructioncode or part of the program (or combination thereof) which is executedvia the operating system. In addition, various other peripheral devicesmay be connected to the computer platform such as an additional datastorage device and a printing device.

It is to be understood that, because some of the constituent systemcomponents and method steps depicted in the accompanying figures arepreferably implemented in software, the actual connections between thesystem components (or the process steps) may differ depending upon themanner in which the present invention is programmed.

FIG. 1 is a block diagram of a computer processing system 100 to whichthe present invention may be applied according to an embodiment of thepresent invention. The system 100 includes at least one processor(hereinafter processor) 102 operatively coupled to other components viaa system bus 104. A read-only memory (ROM) 106, a random access memory(RAM) 108, an I/O interface 110, a network interface 112, and externalstorage 114 are operatively coupled to the system bus 104. Variousperipheral devices such as, for example, a display device, a diskstorage device(e.g., a magnetic or optical disk storage device), akeyboard, and a mouse, may be operatively coupled to the system bus 104by the I/O interface 110 or the network interface 112.

The computer system 100 may be a standalone system or be linked to anetwork via the network interface 112. The network interface 112 may bea hard-wired interface. However, in various exemplary embodiments, thenetwork interface 112 can include any device suitable to transmitinformation to and from another device, such as a universal asynchronousreceiver/transmitter (UART), a parallel digital interface, a softwareinterface or any combination of known or later developed software andhardware. The network interface may be linked to various types ofnetworks, including a local area network (LAN), a wide area network(WAN), an intranet, a virtual private network (VPN), and the Internet.

The external storage 114 may be implemented using a database managementsystem (DBMS) managed by the processor 102 and residing on a memory suchas a hard disk. However, it should be appreciated that the externalstorage 114 may be implemented on one or more additional computersystems. For example, the external storage 114 may include a datawarehouse system residing on a separate computer system.

Those skilled in the art will appreciate that other alternativecomputing environments may be used without departing from the spirit andscope of the present invention.

Referring to FIG. 2, a clinical trials brokerage 250 is illustrated. Theclinical trials brokerage 250 is shown operatively connected to a datarepository which contains patient information typically collected fromone or more health care organization, such as hospitals. This datarepository is called a structured clinical patient record (CPR) 280. Invarious embodiments of the present invention, a plurality of drugcompanies, such as drug company 210, request lists of persons meetingspecified criteria for clinical trials. The structured CPR 280 is thenconsulted to obtain the lists of persons meeting the specified criteria.

The specified criteria may include probability information, thusallowing the selection of patients likely to meet the specified criteriafor the clinical study (e.g., 90% likelihood of diabetes, 70% likelihoodof hypertension). In this case, the relevant patient records wouldinclude probabilistic information.

Furthermore, persons may still be selected even though not allinformation needed to determine whether a patient qualifies in allrespects for a clinical trial is present. In this case, the list wouldinclude “persons of interest” some of whom might later be excluded fromparticipating in the clinical trial for various reasons. Informationabout each person meeting the selection may additionally be provided,including information about other clinical trials that the personparticipated in and whether a placebo was administered.

The system may keep track of a plurality of clinical trials, andmaintain a list of person who were administered a placebo instead of thedrug being tested. In many cases, a person is disqualified from a trialif he or she participated in a trial for a similar drug; however, if itis determined that a placebo was administered, the system may beconfigured to not exclude the person. In other cases, the system wouldprovide information about the trial(s) that the person participated in.

A physician, such as physician 230, may be contacted if one of theirpatients meets the specified criteria for a clinical trial. Prior toreleasing information to a drug company, it is generally necessary toobtain agreement of the patient's physician and an informed consent ofthe patient to participate in the trial. For example, the physician 230may recommend to a patient that a clinical trial being conducted by thedrug company 210 would be beneficial. The details of the trial may havebeen forwarded to the physician 230. Furthermore, physicians may benotified of their Institutional Review Board (IRB) statuses (e.g.,‘approved’, ‘pending’, or ‘not approved’. Expiration dates of theirstatus may be forwarded to approved physicians.

The clinical trials brokerage 250 can be notified that the patientprovided an intent to participate. When the necessary informed consentinformation is obtained, the clinical trials brokerage 250 can providethe identity of the patient (and other patient information) to the drugcompany 210.

Preferably, the structured CPR 280 is populated with patient informationusing data mining techniques described in “Patient Data Mining,” by Raoet al., Attorney Docket No. 2001P20906US01, copending U.S. patentapplication Ser. No. 10/287,055, filed herewith, which is incorporatedby reference herein in its entirety.

That disclosure teaches a data mining framework for mining high-qualitystructured clinical information. The data mining framework includes adata miner that mines medical information from a computerized patientrecord based on domain-specific knowledge contained in a knowledge base.The data miner includes components for extracting information from thecomputerized patient record, combining all available evidence in aprincipled fashion over time, and drawing inferences from thiscombination process. The mined medical information is stored in astructured computerized patient record.

To determine the specified criteria for the clinical study, multipledata sources typically need to be consulted. For example, to determinewhether the patient is diabetic, the system might have to examine thefollowing information:

(a) ICD-9 billing codes for secondary diagnoses associated withdiabetes;

(b) drugs administered to the patient that are associated with thetreatment of diabetes (e.g., insulin);

(c) patient's lab values that are diagnostic of diabetes (e.g., twosuccessive blood sugar readings over 250 mg/d);

(d) doctor mentions that the patient is a diabetic in the H&P (history &physical) or discharge note (free text); and

(e) patient procedures (e.g., foot exam) associated with being adiabetic.

As can be seen, there are multiple independent sources of information,observations from which can support (with varying degrees of certainty)that the patient is diabetic (or more generally has somedisease/condition). Not all of them may be present, and in fact, in somecases, they may contradict each other. Probabilistic observations can bederived, with varying degrees of confidence. Then these observations(e.g., about the billing codes, the drugs, the lab tests, etc.) may beprobabilistically combined to come up with a final probability ofdiabetes. Note that there may be information in the patient record thatcontradicts diabetes. For instance, the patient is has some stressfulepisode (e.g., an operation) and his blood sugar does not go up.

It should be appreciated that the selection of patients for clinicaltrials may be based on probabilistic information. Thus, a list ofpatients that meet the specified criteria may comprise a list ofpatients likely (e.g., according to a particular degree of confidence)to have met the criteria for the clinical trial.

Since it may be necessary to obtain additional information or to verifyinformation about a participant, the clinical trials brokerage 250 mayoutput, or otherwise provide, questionnaires. These questionnaires maybe used to ascertain qualifications for the clinical trial. For example,the patient may be asked to provide a detailed family history ofparticular diseases.

In addition to providing a list of persons meeting the specifiedcriteria, the clinical trials brokerage 250 may also calculate variouscharges and fees. For example, participating physicians may need to becompensated. The drug company may be charged a fee for the list.Additionally, participants in the clinical trial may also becompensated.

In various embodiments of the present invention, lists of persons whoare pre-qualified for certain types of clinical trials may be generated.These lists of pre-qualified individuals may be made available to drugcompanies or other entities interested in conducting a clinical trial.

Referring to FIG. 3, an alternate embodiment of the present invention isillustrated. In this embodiment, a clinical trials brokerage 350 is ableto access a structured CPR 380 containing mined structured patientinformation, and also a clinical trials database 390 containinginformation about various clinical trials. The information in theclinical trials database 390 may include information regarding thequalifications for clinical trials along with other informationregarding the trials. A patient, such as patient 335, may requestinformation about a particular clinical trial. The patient may eitherdirectly access the clinical trials brokerage 350 or go through aphysician, such as physician 330. The clinical trials brokerage 330 mayaccess the structured CPR 380 (populated with information in the samemanner as the CPR 280) to retrieve information about the patient, andattempt to match clinical trials of interest to the patient based on themedical history of the patient and available trials.

Referring to FIG. 4, a flow diagram outlining an exemplary technique forselecting a person for a clinical trial is illustrated. Beginning atstep 401, a person is selected from among a set of persons meetingspecified criteria. This step may include receiving a request for a listof persons meeting specified criteria for a clinical trial, andretrieving a set of patient records from a data source to determinepersons meeting the specified criteria.

For example, a drug company might be interested in selecting black maleswho are diabetic and have had a heart attack within the last threeyears. This might be used to test a new drug.

Using conventional approaches, satisfying the above-mentioned selectioncriteria could be difficult because computerized hospital databasesgenerally do not store such information. However, by employing the datamining techniques described in “Patient Data Mining,” by Rao et al.,Attorney Docket No. 2001P20906US01, copending U.S. patent applicationSer. No. 10/287,055, filed herewith, a structured CPR can be populatedwith such patient information, thus allowing this selection criteria tobe satisfied.

In step 402, the person's physician can be notified that the person hasbeen selected for the clinical trial. At this point, a hospital'sInstitutional Review Board (IRB) can also be notified. The physician canalso be notified if IRB approval has already been granted for this trialat this site, or if he needs to wait for the IRB approval for thistrial. Next, in step 403, a determination is made as to whether thephysician will participate in the study. If it is determined that thephysician will participate, control continues to step 404; otherwisecontrol terminates at step 408.

In step 404, the person is notified that he or she may qualify for theclinical trial. The patient can be directly contacted, or, indirectlycontacted through a physician. At this point, the patient may be givendetailed information about the clinical trial. The patient may be askedfor additional information, such as through a questionnaire. Thequestionnaire may be used to determine qualification for the studyand/or as a way to obtain additional useful information.

Next, in step 405, a determination is made as to whether the personindicated a desire to participate in the clinical trial. If the personnotified his or her physician of an intent to participate, controlcontinues to step 406; otherwise control terminates at step 408.

In step 406, release information is obtained. At this point the personmay be provided with a consent form or be directed to complete oneprovided to him by his or her physician. Any information regardingparticipant compensation, including reimbursements, may also beprovided. Control continues to step 407.

In step 407, fees and charges may be determined. For instance, theentity requesting the list of patients may be charged an appropriate feefor the list of patients. Furthermore, the physician and trialparticipants may also be compensated for their participation in thestudy. Control continues to step 408 where the operation stops.

As shown in FIGS. 1-4, this invention is preferably implemented using ageneral purpose computer system. However the systems and methods of thisinvention can be implemented using any combination of one or moreprogrammed general purpose computers, programmed microprocessors ormicrocontrollers and peripheral integrated circuit elements, ASIC orother integrated circuits, digital signal processors, hardwiredelectronic or logic circuits such as discrete element circuits,programmable logic devices such as a PLD, PLA, FPGA or PAL, or the like.In general, any device capable of implementing a finite state machinethat is in turn capable of implementing the flowchart shown in FIG. 4can be used to implement this system.

Although illustrative embodiments of the present invention have beendescribed herein with reference to the accompanying drawings, it is tobe understood that the invention is not limited to those preciseembodiments, and that various other changes and modifications may beaffected therein by one skilled in the art without departing from thescope or spirit of the invention.

1. A method for maximizing patient opportunity to participate inclinical trials, the method comprising: (a) maintaining by a brokerage alist of patients administered a placebo in a first clinical trial; and(b) including by the brokerage the patients of the list forconsideration of a second clinical trial, the second clinical trialdifferent than the first clinical trial.
 2. The method of claim 1wherein (a) and (b) are preformed with a machine.
 3. The method of claim1 further comprising: (c) determining with a machine whether thepatients meet criteria for the second clinical trial.
 4. The method ofclaim 1 further comprising: (c) retrieving patient information with amachine from multiple, different types of data sources; and (d)determining whether the at least one patient meets criteria for thesecond clinical trial as a function of the patient information andinclusion on the list.
 5. The method of claim 1 wherein (b) comprisesincluding where a first drug for the first clinical trial is similar toa second drug for the second clinical trial.
 6. A system for maximizingpatient opportunity to participate in clinical trials, the systemcomprising: a database of a list of patients administered a placebo in afirst clinical trial; and a machine operable to determine eligibility ofthe patients for a second clinical trail as a function, at least inpart, of inclusion of the patients on the list, the second clinicaltrial different than the first clinical trial.
 7. The system of claim 6wherein the machine is operable to determine whether the patients meetcriteria for the second clinical trial.
 8. The system of claim 6 whereinthe machine is operable to retrieve patient information from multiple,different types of data sources and is operable to determine theeligibility as a function of the patient information.